nutrient

The data set contains the measurements of nutrients in several types
 of meat, fish and fowl.

datasets

The main function kcca implements a general framework for
k-centroids cluster analysis supporting arbitrary distance measures
and centroid computation. Further cluster methods include hard
competitive learning, neural gas, and QT clustering. There are
numerous visualization methods for cluster results (neighborhood
graphs, convex cluster hulls, barcharts of centroids, ...), and
bootstrap methods for the analysis of cluster stability.

Friedrich Leisch

flexclust

Flexible Cluster Algorithms

Evgenia Dimitriadou

Bettina Gruen

nutrient function

A data frame with 27 observations on the following 5 variables.<dl class="dl-horizontal">
 <dt><code>energy</code></dt><dd>Food energy (calories).</dd>
 <dt><code>protein</code></dt><dd>Protein (grams).</dd>
 <dt><code>fat</code></dt><dd>Fat (grams).</dd>
 <dt><code>calcium</code></dt><dd>calcium (milli grams).</dd>
 <dt><code>iron</code></dt><dd>Iron (milli grams).</dd>
 </dl>

Format

Nutrients in Meat, Fish and Fowl — nutrient

A data frame with 27 observations on the following 5 variables.<dl class='dl-horizontal'>
 <dt><code>energy</code></dt><dd>Food energy (calories).</dd>
 <dt><code>protein</code></dt><dd>Protein (grams).</dd>
 <dt><code>fat</code></dt><dd>Fat (grams).</dd>
 <dt><code>calcium</code></dt><dd>calcium (milli grams).</dd>
 <dt><code>iron</code></dt><dd>Iron (milli grams).</dd>
 </dl>

nutrient: Nutrients in Meat, Fish and Fowl

Description

Usage

Arguments

Format

References